You want to obtain a subset of data from a larger data set, with equally represented subgroups within the subset. Which node would you use to accomplish this task?

Question

Options

• AAnalysis node
• BPartition node
• CEnsemble node
• DSample node

• A
  5% (2)
• B
  3% (1)
• C
  3% (1)
• D
  89% (34)

Explanation

Option D (Sample node) is correct because it allows you to draw a subset from a larger dataset using stratified sampling, which ensures that each subgroup is proportionally or equally represented in the output - exactly what the question describes.

Why the distractors are wrong:

• A. Analysis node - performs statistical computations and summaries on data; it does not extract or balance subsets.
• B. Partition node - splits data into training, validation, and test sets for model building, but does not control subgroup balance when pulling a subset.
• C. Ensemble node - combines predictions from multiple models to improve accuracy; it operates on model outputs, not raw data sampling.

Memory tip: Think of "Sample" literally - when you need a sample that fairly represents every group, the Sample node is your tool. Associate "balanced subgroups" with "stratified sampling" and remember that only the Sample node gives you control over how data is selected, not just where it goes (Partition) or what is computed from it (Analysis).

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